Is it ever ok to use Seurat for clustering bulk samples?
I am looking at FPKM data from ~750 bulk RNA-seq samples generated using
Cufflinks. As suggested for FPKM data, I manually input log transformed data to the
@data slot [
cd138_bm@data <- log(firstname.lastname@example.org + 1)] and skip the
NormalizeData() function. I then use functions
FindAllMarkers in their usual ways to find clusters & cluster markers. My clustering results are quite reasonable, and reflect published work clustering similar samples.
What are the potential pitfalls of using these Seurat functions on bulk data? In
FindAllMarkers, would you recommend I use the "negbinom" test? (currently using wilcox) Any other arguments you would recommend changing from the default?